There has been a
tremendous amount of geologic investigation in Precambrian rocks exposed both
across the state of Colorado and throughout the Rocky Mountains in general.
These rocks are still sources of great interest to the geologic community
because they represent the earliest existence of our continent. They hold
information about how large continental masses are assembled and stabilized, the
internal structure of the earth's lithosphere, and other deep crustal
processes that cannot be directly studied in more modern and recent orogenic
systems like the Himalayas and the Tibetan Plateau. In preparing geologic
maps, field geologists rely on traditional hand drafting or, more recently, use
computer graphics software (i.e., Illustrator, Canvas, Corel) to produce
two-dimensional maps. These maps often contain exquisite detail and can be
quite elegant, but they can obscure the various data and observations that
underlie or accompany the mapped features. These data are typically
published, but culling through the literature can be a laborious task.
Furthermore, finding the most up-to-date information can be even harder.
My main objective for this project was to use ArcGIS as a tool to bridge
geologic mapping with all available analytical data (both published and
unpublished) to produce an up-to-date, data-rich, and flexible map document for
Precambrian rocks in southern Colorado. Such a
map product would be a tremendous resource to all
geologists studying these kinds of rocks in this region, and ideally it might
serve as a model for future work integrating geologic mapping with other types
of geologic data.

This particular project focuses on a part of southern Colorado contained within the
Pueblo 1x2 degree topographic sheet and the northern half of the Trinidad 1x2
degree sheet. The geographic features contained within this area include
the northern Sangre de Cristo Mountains, Wet Mountains, Arkansas River Gorge,
and Salida area. While the Precambrian encompasses a tremendous span of
geologic time from the beginnings of the earth ~4.7 billion years ago (Ga, or Giga
annum) to the explosion of life ~550 million years ago (Ma, or Mega annum),
exposures in southern Colorado are limited to a part of the Precambrian called
the Proterozoic (~2500 Ma - 550 Ma). For my dissertation research and this
project, I am most interested in identifying and constraining tectonic events
(magmatism, deformation, and metamorphism) that occurred in the Paleoproterozoic
(ca. 1700 Ma) and in the Mesoproterozoic (ca. 1400 Ma) across the Rocky
Mountains. The project will contain three main elements. First, it
will contain a geologic basemap for the area that shows the various Precambrian
rock units exposed and contains some information about those exposures (unit
name, rock type, etc.). Second, the map will contain elevation data, most
likely in the form of contours of various intervals. Third, the map
document will contain a series of databases that contain information like
radiometric ages, isotopic data, and the like for various locations across the
area. Once complete, the map will not only contain the traditional geology
and topography that is present in traditional geologic maps, but a wealth of
analytical data will also be displayed spatially and allow for point-and-click
identification of geologic features and associated data. If all works
well, this map document will represent a large step towards bridging the gap
between traditional geologic mapping and the tremendous body of published and
in-progress data and observations that underlie the mapping. I do not
foresee the map ever being "finished" because our knowledge base
continues to grow and our ideas evolve. However, I think one of the real
benefits of a project like this will be its flexibility in that the map should
be relatively easy to update as new data emerge and interpretations
change.

The main sources of data for this project are 1) the geologic map of Colorado in ARC/INFO format (U.S.
Geological Survey Open-File Report OF-92-507); 2) digital elevation
data for a selected region of southern Colorado downloaded from the National
Elevation Dataset; and 3) database files and web pages constructed with information
culled from published geologic literature and from other unpublished research.

The geologic map of
Colorado was a challenge to work with because ArcGIS 8.2 was unable to read the
Arc/INFO macros included with the downloaded data. These macros are
intended to rebuild the map including scales, index, and other accessory
features from root data files through a series of Arc/INFO commands.
Instead, I had to build a new geodatabase and add in the downloaded files as feature classes containing a large variety of data (basically 1 feature class
containing all of the map data). Once I added all the data into the
map, I began querying the feature classes and exporting different data types
into individual feature classes. This was a tedious exercise, but it
allowed me to create a map document with more precise layers that could be
turned on or off depending on one's map needs. The most important feature
class I extracted was the one containing only Precambrian rock units exposed
across the state. I was also able to color the Precambrian units with a
simple scheme that is consistent with published maps (e.g., Tweto, 1979) and
allows quick delineation of Archean, Paleoproterozoic, Mesoproterozoic, and
Neoproterozoic components. Click on
the thumbnail below to see the Precambrian geology of Colorado.

Map
of Precambrian exposures across Colorado

Once I established the
basemap, I built a number of databases with data and information gathered from the published literature
(e.g., Bickford et al., 1989a; Bickford et al., 1989b; Sabin, 1994) and some that I have collected and
generated myself as part of my dissertation research. The most critical
data are radiometric ages, and ages from the U-Pb system are particularly
important because of high closure temperatures for Pb retention (~900 degrees C)
and relatively slow rates of radioactive decay of parent U to daughter Pb.
These data tell us precisely when certain rocks were
formed and/or metamorphosed, and there is a wealth of high quality data across the
area. Thus, the main table includes individual sample numbers (essential
as a unique identifier when relating tables in ArcGIS), rock name and type, age
with errors, radiogenic system, any descriptive information available, and the
appropriate reference. Other tables include Sm-Nd and Rb-Sr isotopic data
along with sample identification, etc. All of these tables also include
latitude and longitude for the samples taken either from published maps or from
field measurements. These geographic coordinates allowed me to import the
data tables into the map document and to project the sample points
properly. Click on the thumbnail below to see sample tables. In the
web pages constructed for different areas across the study region, I included
field photographs of the different rock types, larger scale photographs of
distinctive outcrop features, and plots summarizing the various age data and
isotopic data. To view a sample web page, click here.
I will discuss linking the web pages with the map document in the following
section.

Sample geochronology and isotopic data tables
for southern Colorado

I initially planned to
add topography to the geologic basemap through commercial digital topographic
map software put out by iGage Mapping Corporation. Standard U.S.
Geological Survey 7.5' quadrangles were ideal because these are the standard
basemaps for most geological mapping, and they include a variety of practical
information beyond detailed topography like forest and wilderness boundaries,
towns, hydrography, etc. However, these bitmap images, once seamed to cover my
area of interest, took up cumbersome, and in some cases impossible (gigabytes),
amounts of space. Even seaming lower resolution 1:100,000 and 1:250,000
maps still created huge bitmap files. As a result, I turned to the National
Elevation Dataset and downloaded digital elevation data covering part of
southern Colorado and derived topographic contours from these data using the
Spatial Analyst extension in ArcMap. I was initially turned off by the
frustration of downloading 10 Mb parcels of data through a fairly convoluted
interface and ordering process. However, I recently discovered an new
enhanced version of the Seamless
Data Distribution System that allows downloading of unlimited quantities of
DEM, SRTM and NLCD data (as big as you are willing and able to download and
store) in real time. I was able to download a split block of data
that covers my entire area (~100 Mb), whereas previously it would have taken 10
or more 10 Mb parcels of data and the associated download problems. I also
downloaded a small block of Shuttle Radar Topography Mission (SRTM) elevation
data in an area of the Sangre de Cristo Mountains where I am doing my
dissertation research to qualitatively compare the quality of the two datasets.
Click on the thumbnail below to view some examples of the DEM data and Spatial
Analyst products with a brief discussion of the two datasets.

One benefit of the project
that became clear rather quickly was its flexibility. As I mentioned
earlier, I want this map document to include the most current information. If used as a work in progress
for researchers working in the Precambrian of southern Colorado, a geodatabase
could conceivably contain the most up-to-date information available, even if
some or much of it has yet to be published. The published Geologic Map of
Colorado (Tweto, 1979) has a number of features that are out of date, and these
features were easily changed and updated based on published information in
ArcMap using the editor toolbar. For example, the Oak Creek pluton
in the northern Wet Mountains was originally mapped as a Paleoproterozoic
intrusion (~1.7 Ma) based on its texture and appearance. However, it has
since been dated by Bickford et al. (1989a), and they demonstrate that the
pluton crystallized at 1436 Ma.
Simply changing the value in the "UNIT" field of the attribute table
from Xg (Paleoproterozoic granite) to Yg (Mesoproterozoic granite) made the
update complete and changed the symbology of the polygon representing the
granite to the appropriate color.

Once all of the different data
components were created and properly formatted, I merged them all into one map
document and began testing for consistency among the various datasets and to see
what was possible within the ArcGIS framework. To a first order, the map
itself is incredibly interesting itself regardless of the amount of data
embedded or contained within it. With a simple look at the map, one can
tell whether exposures occur in steep cliffs or subtle hills and where the best
point of access might be. Published regional-scale maps rarely include
detailed topographic information. The variety of contour intervals
produced also allows for analysis at multiple scales. Because the
elevation data are contained within the map document, one could easily perform a
number of different analyses. For example, if someone were interested in
geomorphology rather than Precambrian geology, that person could conceivable
analyze the relationship between rock type or rock age with average elevation or
slope. The data also allow field geologist to recognize more practical
mapping issues like whether outcrops occur along grassy slopes or in steep cliff
faces.

When all of the components of
the project came together, I was thrilled to discover what was possible in
ArcGIS. By using the identify tool in ArcMap, one can click on a
particular geologic feature and immediately see what unit it is mapped as.
Where there is a data point, one can click on the point and quickly see the
sample information, rock type, outcrop descriptions, and the rock's age and
associated errors. If there is isotopic data associated with the sample,
this information is related and shows up in the identify box as well.
Ideally, with a few clicks one could see the age, initial Sr ratios, epsilon Nd
values, and Nd model ages for one sample all in the context of a geologic
map. One can also query the map to isolate features of interest and export
them as individual map layers or query the attribute tables to isolate
particular values or check the statistics. Some sample results of such
analysis is discussed briefly below. For a graphical example of this
discussion, click the thumbnail below.

Identifying
map features and related data in ArcMap

I was able to take the project a
step further when I finally figured out how to hyperlink in ArcMap. I
built web pages containing photographs and data plots for various samples across
the area, and I was able to link those through the identify table in
ArcMap. As a result, for certain samples, one can right-click on the
sample identifier in the identify box and see the hyperlinks that are associated
with the feature. So not only does the map contain abundant data, but it
is also linked via the web to resources like field and thin section photographs,
data plots, and other useful types of information. If all of the features
in the map do not have hyperlinks, it can be difficult to recognize which
features do have associated web pages. However, there is a hyperlink tool
in the identify toolbar that looks like a lightning bolt that one can use to
identify which features in a map document have associated hyperlinks. For
a graphical example of hyperlinking in ArcMap, click the thumbnail below.

Linking
features in ArcMap to the world wide web.

Finally, I want to include a hint of the capability of
this project to answer particular geologic questions. I mentioned earlier
that I was interested in identifying and constraining the occurrence of tectonic
events during the Paleoproterozoic (ca. 1700 Ma) and the Mesoproterozoic (ca.
1400 Ma). By running a quick statistical analysis of the attribute "AGE_MA"
of the geochronology features, it becomes clear that there are distinct pulses
of magmatism and/or metamorphism during these two time periods with a distinct
hiatus in between. It also is clear that the peaks of activity are
centered around ~1435 Ma and ~1670-1690 Ma. This is very powerful
information gathered rather quickly from the attribute table. Furthermore,
by querying the data by age distribution, it is possible to select and export
rock units with these ages to look at their distribution across the region.

Distribution
of Paleoproterozoic (ca. 1700 Ma) rocks across Colorado.

Distribution
of Mesoproterozoic (ca. 1400 Ma) rocks across Colorado.

These analytical outputs are just a hint of what is possible with such a
data-rich and interactive map document, and I look forward to exploring its
capabilities in more detail.

I hope it is clear from the discussions above that ArcGIS
enables the production or compilation of up-to-date, data-rich, and flexible map
documents. There is a tremendous amount of effort that goes into creating
such a project, but its benefits are endless. The ability to display
analytical data in the context of geologic mapping is critical in itself, but
the added abilities to display the data and mapping with elevation data and to
link the data and maps to other types of information via the World Wide Web
provides endless opportunities for enhancing research capabilities and geologic
mapping and modeling. Not only does this
database contain the current state of knowledge, but I also believe that it will
be relatively easy to update as new data and more refined studies emerge.
This map and database and others like it can provide user-friendly access to a wealth of geologic information that otherwise
would have to be culled from the published literature and allow
construction of maps that can be themed to address particular research
questions.

This
project will continue to be a work in progress as new data and interpretations
will continue to emerge. I hope that it can also be expanded to include
the Precambrian of the entire state of Colorado and perhaps ultimately the Rocky
Mountains and southwestern United States. Furthermore, I hope to add other
types of data including radiometric age data for all
systems available (e.g., U-Pb zircon, U-Pb monazite, Ar-Ar, Pb-Pb), geochemical
and additional isotopic data, and perhaps some interpretation of tectonic or geologic
environment. I would also like to explore ways to incorporate more
detailed mapping (i.e., 1:24k or 1:12k scale mapping) into regional-scale
geologic maps. Finally, another critical issue involves the dissemination
of these types of projects. This type of data product will be most useful
if anyone interested has access. Perhaps publishing on CD-ROM or DVD-ROM
might allow enough access, and these products could be updated and re-released
as significant advances are made. The World Wide Web is probably the ideal
venue for publishing and maintaining these types of databases, but we're not
there yet. This project certainly demonstrates (at least to me) that field
geologists should head in the digital direction.